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6160Re: [decentralization] artificial immune system

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  • Rod Price
    Oct 3, 2002
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      I've attached the conference paper. It's contribution to the field
      lies in the fact that Keith's implementation is distributed over a
      small network. The fundamental ideas are found elsewhere (see the
      link below).

      So, an executive summary...

      An artificial immume system is a model loosely based on the human
      immune system. The objective is to rapidly identify invading
      antigens (viruses, bacteria, or offending IP addresses) so that
      other systems can halt the attack. In the body, this is done by
      B-cells which bind specifically to a particular antigen. The trouble
      is, there can only be about 10^8 (100 million!) different varieties
      of B-cell in the body at any given time, but there are 10^12 to
      10^16 possible antigens out there. The B-cells collectively form
      a memory capable of storing 10^8 patterns, but must recognize 10^16

      The body overcomes this problem by attempting to store the *right*
      10^8 patterns, since there are probably not more than 10^8 antigens
      it is likely to encounter. Besides, cells in the body itself
      represent a large set of patterns, and it wouldn't do to have some
      B-cells identify human cells as antigens.

      So, the body manufactures immature B-cells in the thymus. Each new
      B-cell recognizes some pattern in a space of 10^16 possibilities.
      If the immature B-cell recognizes a human cell / pattern, a process
      in the thymus kills it. If the B-cell does not recognize a human
      pattern, it is let loose into the wild (your body).

      Think of the B-cells as initially randomly distributed in this high-
      dimensional (10^16 dimensions) space. Someone sneezes near you and
      a set of antigens (viruses) lands in that space. One or two B-cells
      happen to be near the antigen location and they bind to a few of the
      virus particles. Most of the viruses get by and multiply like crazy,
      causing you to get sick.

      In the meantime, the B-cells that bound to viruses have signaled that
      an attack is in progress. In response, the body begins manufacturing
      copies of those B-cells by the truckload. Now it's a race between
      two exponentially growing populations. Most of the time the B-cells
      win and you get better.

      After the fact, however, the distribution of B-cells in that high-
      dimensional space is no longer random. In the vicinity of the
      antigen pattern the B-cells are very dense. The next time that
      particular antigen attacks (someone you gave your cold to sneezes),
      that thick set of B-cells can grab just about every virus particle
      that got in and kill it. The immune response is very quick and you
      stay healthy.

      So after some time, your B-cells form a distributed memory of the
      antigens you've encountered before. The distribution is thick in
      the regions where likely antigens live and thin in regions where
      they don't live.


      That's how the body does it. Keith implemented his system with
      mobile agents. These agents acted as carriers for digital B-cells,
      moving patterns at random around the network. Antigens were
      recognized in one part of the network, lots of digital B-cells were
      generated in defense, and before long all the machines in the network
      were able to recognize those antigens.

      The trick lies in generating the patterns for the "B-cells" to bind
      to. In the present case it should be quite simple: offending IP
      addresses are the patterns. An attack on one part of the network
      is detected and the appropriate "B-cells" then spread throughout the
      network. The first attack succeeds to a degree but subsequent ones
      fail. Moreover, the system is entirely de-centralized -- nowhere
      can you find a single point of failure. This is achieved by simply
      making each computer in the network act as its own "thymus".

      It's fascinating work. I'm interested to hear what this group thinks
      of it.


      Lucas Gonze wrote:
      > Rod Price wrote:
      >>A co-worker of mine has implemented a de-centralized version of an
      >>artificial immune system that would seem ideal for this application.
      >>The system can recognize "self" and will flag "not-self." I know
      >>this description is vague, but my co-worker isn't around right
      >>now (9:00 pm) to help me out. For details on artificial immune
      >>systems, look at http://www.cs.unm.edu/~forrest/papers.html,
      >>particularly "Architecture for an Artificial Immune System" on
      >>that site.
      > Any chance of getting more of an executive summary, Rod? My first thought
      > is that the idea of 'us' and 'them', as opposed to the 'me' and 'everybody
      > else' that decentralized designs normally use, might be too slippery to
      > work with.
      > (posting that conference paper would be a good thing -- please do!)
      > - Lucas
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